Why This Role Stands Out
This hybrid role offers a significant opportunity to shape the future of AI security within a leading logistics company, building and mentoring a specialized team. You will thrive here if you possess a strong background in AI/ML security architecture and risk management, ready to drive innovative security-by-design principles. Apply to leverage your expertise and make a substantial impact on enterprise-wide AI initiatives.
Quick Overview
Job Description
Ryder System is seeking a Senior Director AI Security to lead strategy and execution of AI and ML security across our transportation and warehousing platforms. You will define AI security architecture, govern model lifecycle risks, and implement controls for data privacy, model integrity, and secure deployment in cloud and edge environments. Partner with cybersecurity, data science, and operations teams to assess threats, respond to incidents, and ensure compliance. You will build and mentor a high-performing team, drive security-by-design for AI solutions, and guide leadership on emerging AI risks in a safety-first logistics environment.
Responsibilities
- Lead enterprise AI and ML security strategy for transportation and warehousing platforms
- Define and maintain AI security architecture, standards, and governance
- Implement controls for data protection, model integrity, and secure deployment
- Collaborate with cybersecurity, data science, and operations on threat modeling and risk mitigation
- Oversee AI-related incident response, monitoring, and compliance activities
- Build and mentor a high-performing AI security team
- Establish security-by-design practices for AI product development
- Advise senior leadership on emerging AI threats, regulations, and best practices
- Develop and track AI security metrics and reporting for stakeholders
- Manage vendor and third-party risk for AI and ML solutions
Required Skills
- AI and ML security architecture
- Cloud security (AWS, Azure, GCP)
- Data protection and privacy (encryption, access control)
- Threat modeling and risk assessment for AI systems
- Secure MLOps and model lifecycle management
- Security governance, compliance, and policy development
- Incident response and security monitoring for AI workloads
- Zero trust and identity/access management
- Secure software development and Dev
- Sec
- Ops
- Team leadership and cross-functional collaboration
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